{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "bearing-grade",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import statsmodels.api as sm\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "import itertools\n",
    "import warnings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "concrete-chrome",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = sm.datasets.co2.load()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "hired-dakota",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DatetimeIndex(['1958-03-29', '1958-04-05', '1958-04-12', '1958-04-19',\n",
      "               '1958-04-26', '1958-05-03', '1958-05-10', '1958-05-17',\n",
      "               '1958-05-24', '1958-05-31',\n",
      "               ...\n",
      "               '2001-10-27', '2001-11-03', '2001-11-10', '2001-11-17',\n",
      "               '2001-11-24', '2001-12-01', '2001-12-08', '2001-12-15',\n",
      "               '2001-12-22', '2001-12-29'],\n",
      "              dtype='datetime64[ns]', length=2284, freq='W-SAT')\n"
     ]
    }
   ],
   "source": [
    "#对引入的数据进行变形\n",
    "index = data.data.index\n",
    "co2=pd.DataFrame(data.data['co2'], index=index, columns=['co2'])\n",
    "print(co2.index)#检查co2的索引"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "greatest-theme",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>co2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1958-03-29</th>\n",
       "      <td>316.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-04-05</th>\n",
       "      <td>317.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-04-12</th>\n",
       "      <td>317.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-04-19</th>\n",
       "      <td>317.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-04-26</th>\n",
       "      <td>316.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001-12-01</th>\n",
       "      <td>370.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001-12-08</th>\n",
       "      <td>370.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001-12-15</th>\n",
       "      <td>371.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001-12-22</th>\n",
       "      <td>371.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001-12-29</th>\n",
       "      <td>371.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2284 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              co2\n",
       "1958-03-29  316.1\n",
       "1958-04-05  317.3\n",
       "1958-04-12  317.6\n",
       "1958-04-19  317.5\n",
       "1958-04-26  316.4\n",
       "...           ...\n",
       "2001-12-01  370.3\n",
       "2001-12-08  370.8\n",
       "2001-12-15  371.2\n",
       "2001-12-22  371.3\n",
       "2001-12-29  371.5\n",
       "\n",
       "[2284 rows x 1 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "co2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "choice-apartment",
   "metadata": {},
   "outputs": [],
   "source": [
    "y = co2['co2'].resample('MS').mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "dated-basketball",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<bound method NDFrame._add_numeric_operations.<locals>.sum of 1958-03-01    False\n",
      "1958-04-01    False\n",
      "1958-05-01    False\n",
      "1958-06-01     True\n",
      "1958-07-01    False\n",
      "              ...  \n",
      "2001-08-01    False\n",
      "2001-09-01    False\n",
      "2001-10-01    False\n",
      "2001-11-01    False\n",
      "2001-12-01    False\n",
      "Freq: MS, Name: co2, Length: 526, dtype: bool>\n"
     ]
    }
   ],
   "source": [
    "print(y.isnull().sum)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "increased-diversity",
   "metadata": {},
   "outputs": [],
   "source": [
    "y=y.fillna(y.bfill())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "suitable-lafayette",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x26700aa70b8>]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,6))\n",
    "plt.title(\"primitive data\",loc=\"center\",fontsize=20)\n",
    "plt.plot(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "color-nature",
   "metadata": {},
   "outputs": [],
   "source": [
    "p=d=q=range(0,2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "chronic-tours",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "p= range(0, 2) d= range(0, 2) q= range(0, 2)\n"
     ]
    }
   ],
   "source": [
    "print(\"p=\",p,\"d=\",d,\"q=\",q)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "seventh-cricket",
   "metadata": {},
   "outputs": [],
   "source": [
    "pdq = list(itertools.product(p,d,q))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "executed-significance",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[(0, 0, 0), (0, 0, 1), (0, 1, 0), (0, 1, 1), (1, 0, 0), (1, 0, 1), (1, 1, 0), (1, 1, 1)]\n"
     ]
    }
   ],
   "source": [
    "print(pdq)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "printable-tracy",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
